Compressed shaping is enabled by a shaping encoding that is sensitive to the source entropy. As data compression allocates short bit patterns to frequently occurring source words, compressed shaping allocates amplitudes with small energy to such frequent source words.
This compression feature is similar to burst signalling in time-domain multiple access [1]}, i.e., optical power variation depending on the traffic.
Compressed shaping is a fixed-length to fixed-length conversion, and the average energy of channel input symbols is reduced for source information sequences having a small entropy.
We do not need an operational mode change such as updating the source statistics based on prior knowledge, although this would be a kind of data compression.
Our previously proposed look-up table (LUT)-based hierarchical DM [2]} and following works [3]}, [4]} are applicable for this purpose without significantly increased complexity, but rather a reordering of the LUT entries.
can be applied for this purpose by reordering the LUT entries without significantly increased complexity.
The proposed technique can reduce the rate losses associated with source and channel coding compared with state-of-the-art DM schemes such as constant-composition DM (CCDM) [5]}, or reduce the power consumption in the FEC at a given information rate and signal-to-noise ratio (SNR) by relaxing the FEC performance.
We also report a field programmable gate array (FPGA) implementation, realtime evaluation and the hardware demonstration results for compressed shaping 16- and 64-QAM at system throughputs of 153 and \(113\,\mathrm {Gb/s}\) , respectively.
